Investigating Netflix Movies and Guest Stars in The Office

# Create the years and durations lists years = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020] durations = [103, 101, 99, 100, 100, 95, 95, 96, 93, 90] # Create a dictionary with the two lists movie_dict = {'years': years, 'durations': durations} # Print the dictionary movie_dict

# Import pandas under its usual alias import pandas as pd # Create a DataFrame from the dictionary durations_df = pd.DataFrame(movie_dict) # Print the DataFrame durations_df

# Import matplotlib.pyplot under its usual alias and create a figure import matplotlib.pyplot as plt fig = plt.figure() # Draw a line plot of release_years and durations plt.plot(durations_df['years'], durations_df['durations']) # Create a title plt.title("Netflix Movie Durations 2011-2020") # Show the plot plt.show()

# Read in the CSV as a DataFrame netflix_df = pd.read_csv("datasets/netflix_data.csv") # Print the first five rows of the DataFrame netflix_df[0:5]

# Subset the DataFrame for type "Movie" netflix_df_movies_only = netflix_df[netflix_df['type'] == 'Movie'] # Select only the columns of interest netflix_movies_col_subset = netflix_df_movies_only[['title', 'country', 'genre', 'release_year', 'duration']] # Print the first five rows of the new DataFrame netflix_movies_col_subset[0:5]

# Create a figure and increase the figure size fig = plt.figure(figsize=(12,8)) # Create a scatter plot of duration versus year plt.scatter(netflix_movies_col_subset["release_year"], netflix_movies_col_subset["duration"]) # Create a title plt.title("Movie Duration by Year of Release") # Show the plot plt.show()

# Filter for durations shorter than 60 minutes short_movies = netflix_movies_col_subset[netflix_movies_col_subset['duration'] < 60] # Print the first 20 rows of short_movies short_movies[0:20]

# Define an empty list colors = [] # Iterate over rows of netflix_movies_col_subset for lab, row in netflix_movies_col_subset.iterrows(): if row['genre'] == "Children": colors.append("red") elif row['genre'] == "Documentaries": colors.append("blue") elif row['genre'] == "Stand-Up": colors.append("green") else: colors.append("black") # Inspect the first 10 values in your list colors[0:10]

# Set the figure style and initalize a new figure plt.style.use('fivethirtyeight') fig = plt.figure(figsize=(12,8)) # Create a scatter plot of duration versus release_year plt.scatter(netflix_movies_col_subset["release_year"], netflix_movies_col_subset["duration"], c=colors) # Create a title and axis labels plt.title("Movie duration by year of release") plt.xlabel("Release year") plt.ylabel("Duration (min)") # Show the plot plt.show()

# Are we certain that movies are getting shorter? are_movies_getting_shorter = "maybe"